Displaying 10 of 109 results for "Emmanuel Mhike Hove" clear search
I am a marine environmental scientist by training (U Oldenburg, 2001) with a PhD in atmospheric physics (U Wuppertal, 2005) and a strong modeling focus throughout my career.
I have built models (C, C++) for understanding the regional transitions from hunting-gathering subsistence to agropastoral life styles throughout the world. The fundamental principle of these models is to consider aggregate traits of populations, such as the preference for a subsistence style. I applied these models to the European “Wave of Advance”, to the disintegration of the urban Indus civilisation and to the differential emergence of agropastoralism in the Americas versus Europe, but also globally. An interesting outcome of these models are global and reginoally resolved prehistoric CO2 emissions caused by the land use transitions.
I have built and applied models for understanding the ecological relations and biogeochemical flows through the North Sea ecosystem. Also for this research I apply trait-based models, looking at traits such as vertical positioning or energy allocation. As an outcome, I have, e.g., estimated the biomass of blue mussels in the North Sea and quantified the effect of Offshore Wind Farm biofouling on the sea’s produtivity.
I led the development of the Earth System coupler MOSSCO, leveraging ESMF technologies. I like to rip legacy models apart and reconstruct them with interoperability and reusability by design. I contribute to building the next-generation modular hurricane forecasting system.
As a member of the Open Modeling Foundation (OMF), I am an evangelist of good scientific software practices, and educate and publish about improving underlying assumptions, stating clear purposes, keeping models simple and aquiring tools to further good practices.
My research centers on isolating how and to what extent political institutions themselves shape policy. I use computational modeling (agent-based and simulation) to gain theoretical leverage on the issue. This approach allows me to place groups of actors with given preferences into different institutional settings in order to gauge the effect of the rules of the game on political outcomes. Most of my research examines the ways in which legislative processes affect issues of political economy, such as income redistribution.
Hi. I’m Wolf. I’m the Argelander (Tenure-Track Assistant) Professor for Integrated System Modeling for Sustainability Transitions at the University of Bonn, Germany.
We reshape human-environment modeling to identify critical leverage points for sustainability transitions.
Cooperation at scale – in which large collectives of intelligent actors in complex environments seek ways to improve their joint well-being – is critical for a sustainable future, yet unresolved.
To move forward with this challenge, we develop a mathematical framework of collective learning, bridging ideas from complex systems science, multi-agent reinforcement learning, and social-ecological resilience.
My core research interest is to understand how humans and other living creature perceive and behave; respond and act upon their environment and how this dynamic interplay shapes us into who we are. In recognition of the broad scope of this question I am a strong believer in the need for inter- and multi-disciplinary approaches and have worked at research groups in a wide range of departments and institutions, including university departments of Physics as well as Psychology, a bio-medical research lab, a robotics research laboratory and most recently the RIKEN Brain Science Institute. Though my work has primarily taken the form of computational neuroscience I have also performed psychophysical experiments with healthy human subjects, been involved in neural imaging experiments and contributed towards the development of a humanoid robot.
Based on the philosophy of ‘understanding through creating’ I believe that bio-mimetic and biologically inspired computational and robotic engineering can teach us not only how to build more flexible and robust tools but also how actual living creatures deal with their environment. I am therefore a strong believer in the fertile information exchange between scientific as well as engineering research disciplines.
I am an agent-based simulation modeler and social scientist living near Cambridge, UK.
In recent years, I have developed supply chain models for Durham University (Department of Anthropology), epidemiological models for the Covid-19 pandemic, and agent-based land-use models with Geography PhD students at Cambridge University.
Previously, I spent three years at Ludwig-Maximillians University, Munich, working on Human-Environment Relations and Sustainability, and over two and a half years at Surrey University, working on Innovation with Nigel Gilbert in the Centre for Research in Social Simulation (CRESS). The project at Surrey resulted in a book in 2014, “Simulating Innovation: Computer-based Tools for Rethinking Innovation”. My PhD topic, modeling human agents who energise or de-energise each other in social interactions, drew upon the work of sociologist Randall Collins. My multi-disciplinary background includes degrees in Operational Research (MSc) and Philosophy (BA/MA).
I got hooked on agent-based modeling and complexity science some time around 2000, via the work of Brian Arthur, Stuart Kauffman, Robert Axelrod and Duncan Watts (no relation!).
As an agent-based modeler, I specialize in NetLogo. For data analysis, I use Excel/VBA, and R, and occasionally Python 3, and Octave / MatLab.
My recent interests include:
* conflict and the emergence of dominant groups (in collaboration with S. M. Amadae, University of Helsinki);
* simulating innovation / novelty, context-dependency, and the Frame Problem.
When not working on simulations, I’m probably talking Philosophy with one of the research seminars based in Cambridge. I have a particular interests when these meet my agent-based modeling interests, including:
* Social Epistemology / Collective Intelligence;
* Phenomenology / Frame Problem / Context / Post-Heideggerian A.I.;
* History of Cybernetics & Society.
If you’re based near Cambridge and have an idea for a modeling project, then, for the cost of a coffee / beer, I’m always willing to offer advice.
My interests is always on the dynamic interactions of human and their habitat (nature/built environment, etc.). At the moment my researches focus on the political-ecology analysis of human-nature interactions and social-ecological systems analysis. I am interested in using Agent-Based Model to support my works. I have been using ABM for quite some years, although not putting too much focus on it at the moment.
Leonardo Grando is a Ph.D. at the University of Campinas (UNICAMP) in Brazil. I am interested in complex systems, agent-based simulation, artificial intelligence, the Internet of Things, programming, and machine learning tools. I have expertise in Netlogo, Python, R, Latex, SQL, and Linux tools.
My Ph.D. work project is an IoT devices (UAVs) swarm agent-based modeling simulation (ABMS) aiming the perpetual flight. The workflow is Netlogo to ABMS simulate, Python and R to data analysis, and I use Latex for my thesis writing.
Intrapreneur and experienced Consultant with a demonstrated history in the energy industry. Skilled in Business Planning, Corporate Finance, Digital Transformation and Analytics. Strong consulting professional focused in Organizational Development and Project Management. I have a degree in Industrial Engineering from the Rio de Janeiro State University (2000) and a master’s degree in Economics from Brazilian Institute of Capital Markets IBMEC (2003). Has experience in the area of Computer Science, with emphasis on Modeling of Complex Systems.
Complex Systems
Agent-based Models
System Dynamics
Innovation
Economics
Organizational Development
Jorge is a PhD candidate of System Design Engineering at the University of Waterloo. His research activities are focused on applying agent-based models on three major areas: 1) financial markets to study the self-regulation capability of artificial markets with interacting investors and credit rating agencies; 2) the efficiency of road networks when users have access to real-time information and are able to adjust their behavior to current conditions; 3) failure probability of nuclear waste containers due to microbial- and chemical-driven corrosion.
My profound interest in networks convinced me to work in these subjects and start my master project on an application of social network analysis for detecting organized fraud in Automobile insurance, which helps to flag groups of fraudsters. The key point of this project is simply to find fraudulent rings, while the most of traditional methods have only taken opportunistic fraud into consideration. My duty in research is to design an algorithm for identifying cyclic components, then to be compared with theoretical ones. This project showed me how networks are used in the analysis of relations.
Displaying 10 of 109 results for "Emmanuel Mhike Hove" clear search